Month November 2013

Apple has sold 700 million iOS devices. Google claims one billion Android device activations. Microsoft has about 1.5 billion Windows users and Facebook about 1.19 billion. LinkedIn has 259 million users and Twitter has 232 million. Amazon has 215 active account holders and PayPal 137 million.

Markets place a value on these users implicitly when company shares are priced. For example, Twitter whose users are worth about $110 or FaceBook’s $98 and LinkedIn at $93.

This consistency suggests a universally accepted value per social media user but what is the value of an ecosystem user? Apple, Google, Microsoft and even Amazon aspire to enable ecosystems which should be seen are more valuable than mere communities. Ecosystems enable a higher level of economic activity because they are unbounded by the medium itself. Any number of media can be created. Or so the theory goes.

If we could determine a value for an ecosystem user we could test it against the going value of a social media user. Fortunately we have enough data to do so.

The total number of iOS devices sold per quarter allows us to measure the install base of device users. With some assumptions regarding the retirement and attrition rate we can get the following history:

Since the total number of iTunes accounts is updated with some regularity I’ve added it to the graph. I’ve also shown on the same graph the total number of iCloud accounts. For calibration, I included survey data showing the number of iPhone users in two regions (US and EU5).

The closing of one and the onset of another era. In this hundredth episode of The Critical Path we look back to some of the big questions we asked and ask them again with hindsight and foresight. They are:

What happens to entertainment in the era of pervasive connectivity and computing?

What happens to privacy when citizenship requires divulging all your secrets to commercial entities?

What happens to the structure of computing when diffusions of innovations are instantly global?

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The graph below shows the Revenue and Operating Income for a select group of companies. The large numbers represent the share price to earnings (trailing twelve months) ratio (P/E or PE ratio).

Of course the P/E ratio hides a lot of subtlety. It mostly fails to account for the fact that earnings are largely a matter of opinion. A company can defer income (as Apple and Microsoft do), it can invest earnings (as Amazon does) and can otherwise avoid declaring it since it’s taxable.

All theoretical and empirical diffusion studies agree that an innovation diffuses along a S-shaped trajectory. Indeed, the S-shaped pattern of diffusion appears to be a basic anthropologic phenomenon.

This observation dates as far back as 1895 when the French sociologist Gabriel Tarde first described the process of social change by an imitative “group-think” mechanism and a S-shaped pattern.[1] In 1983 Everett Rogers, developed a more complete four stage model of the innovation decision process consisting of: (1) knowledge, (2) persuasion, (3) decision and implementation, and (4) confirmation.

Consequently, Rogers divided the population of potential adopters according to their adoption date and categorized them in terms of their standard deviation from the mean adoption date. He presented extensive empirical evidence to suggest a symmetric bell shaped curve for the distribution of adopters over time. This curve matches in shape the first derivative of the logistic growth and substitution curve as shown below.

In the graph above I applied the Rogers adopter characterization to the data we have on the adoption of smartphones in the US. The latest data covering September is included.

Notes:

Tarde was probably influenced by mathematician Pierre François Verhulst who first published the logistic function in 1845 [↩]

For the year ending October Apple’s R&D costs were $4.475 billion. These costs have been rising. Though, as the company explains, not faster than net sales:

The growth in R&D expense was driven by an increase in headcount and related expenses to support expanded R&D activities. Although total R&D expense increased 32% and 39% in 2013 and 2012, respectively, it remained fairly consistent as a percentage of net sales.

[My emphasis]

We can see this in the following graph:

R&D has remained very nearly 3% of sales since at least 2005.

SG&A Expenses barely grew however:

The growth in SG&A during 2013 was primarily due to the Company’s continued expansion of its Retail segment and increased headcount and related expenses, partially offset by decreased spending on professional services.

The change in R&D and SG&A on a full-year basis is shown below.

I emphasized the mention of increases in headcount. We cannot know with any precision what portion of last year’s $15 billion in operating expenses went toward wage expenses since there are other costs such as advertising[1] commissions and public relations in the case of SG&A and outside services, equipment leases, in the case of R&D. However, it’s more likely that wage expenses are a far larger proportion of total R&D than they are of SG&A.

My estimate, based on wage rates, is that there are approximately 15,000 R&D staff at Apple.

If we divide sales by this number we get $11.4 million in sales per engineer.

Notes:

Apple’s advertising expenditures for fiscal 2013 were $1.1 billion or 10% of SG&A or 0.64% of sales. [↩]